Skip to main content
padlock icon - secure page this page is secure

Conditioning of incremental variational data assimilation, with application to the Met Office system

Buy Article:

$52.00 + tax (Refund Policy)

ABSTRACT

Implementations of incremental variational data assimilation require the iterative minimization of a series of linear least‐squares cost functions. The accuracy and speed with which these linear minimization problems can be solved is determined by the condition number of the Hessian of the problem. In this study, we examine how different components of the assimilation system influence this condition number. Theoretical bounds on the condition number for a single parameter system are presented and used to predict how the condition number is affected by the observation distribution and accuracy and by the specified lengthscales in the background error covariance matrix. The theoretical results are verified in the Met Office variational data assimilation system, using both pseudo‐observations and real data.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Document Type: Research Article

Affiliations: Department of Mathematics and Statistics, P.O. Box 220, University of Reading, Reading, RG6 6AX, UK

Publication date: August 1, 2011

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more